Read Matt Chalawsky‘s answer to How detrimental are leaf blowers to air quality in Los Angeles? on Quora
How detrimental are leaf blowers to air quality in Los Angeles?
Matt Chalawsky’s about.me page: About.me/mattchalawsky
Matt is a software engineer and entrepreneur currently living in Los Angeles, California. My interests range from technology to entrepreneurship. I am also interested in food, programming, and DIY.
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Read Matt Chalawsky answer to What are the best arguments for investing in chatbot startups now?
Conversational UI have always been the holy grail of user interfaces (UI) since the movie “2001: A Space Odyssey” came out. This approach more naturally matches the way most people communicate and is a major paradigm shift from conventional UIs.
At the heart of chatbots are Natural language processing (NLP) tools. These tools have been steadily improving and finally reached a point where the economics make sense to build conversational UIs.
Many large companies and investors are betting big that conversational UI is a going to dominate many UIs in the future.
Matt Chalawsky — Are Chatbots and Conversational UI a paradigm shift in UX?
It’s been over a year since Facebook announced it’s Messenger bot initiative. As with most new technologies, there’s a lot of excited at first, but eventually the technology will either prove to be a better user experience or not.
There’s some evidence that Chatbots are gaining traction. This is actually surprising since most chatbots are still fairly unsophisticated and struggle to provide more than a scripted response.
Natural language processing (NLP) has been making huge gains in recent years. NLP allows chatbots to understand the intent of a statement. This is a very difficult problem given that the English language allows so many ways to say the same thing. Luckily for chatbot developers, there are a growing number of NLP tools (i.e. API.ai, Microsoft LUIS, IBM Watson) that solves the most daunting aspects of the problem.
Mobile is the key driver of chatbots today since the mobile user experience (UX) has a low bar, but eventually, as chatbots improve, it’s easy to see chatbots taking over key industries on the desktop as well. Industries with complex vernacular will be the most obvious choice:
My answer to Why does Google suck?
Answer by Matt Chalawsky:
Google Search is in a constant battle between good and evil. Ok, that was too dramatic. But Google’s goals and the goal’s of those in search results are at odds with each other. Google’s goal is to simply organize the world’s information. Most websites simply want to be ranked as high as possible, regardless if they deserve it or not.
This has created entire industries that focus on trying to manipulate Google’s search results, sometimes nefariously. Google has responded by creating multiple organizations to constantly improve (sometimes daily) it’s search rank algorithms and identify policy violators.
This constant cat and mouse game causes Google’s search results to fluctuate. Sometimes the results do “suck”, but that just means that website owners have temporarily gotten the upper hand.
Other Products. I’m assuming this question is about Google’s flagship product, Google Search, since most people associate Google with Search. Google has many products (Android, YouTube, Adsense, etc.), and each of them has their own organization within Google. Each organization is run independently, and thus must be evaluated independently.
BrandYourself offers a step-by-step process of building a strong online presence that looks great when people Google your name.
They took all of their knowledge of in-house managed services team and broke it down into simple guides that range from combating negative search results to building the websites and profiles you need to look great online.
Ad skip feature for characterizing advertisement effectiveness
US 8468056 B1
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing effectiveness of online advertisements inserted into media streams based at least in part on monitoring events indicative of an audience skipping ad streams inserted into the media streams. The methods and systems described in this specification enable tracking the number of impressions prior to detecting events indicative of interest or disinterest for ad streams inserted into a media stream.
External-signal influence on content item performance
US 8706550 B1
Abstract
External-signal influence on content item performance is determined. Content item performance data is received that reflects historic performance of a content item for multiple presentations of the content item. Signal data is received that corresponds to at least one signal that is temporally correlated with the content item performance data and that is external to each user, publisher and content provider involved in any of the presentations. Using the content item performance data and the signal data, an influence value for the signal with regard to the content item is determined. A content item prediction model is modified based on the influence value.
Frequency optimization of advertisement insertion in media streams
US 8583484 B1
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for frequency optimization of advertisement streams. The methods and systems described in this specification may enable determination of an optimal presentation frequency of an ad stream, or a number of times the ad stream is to be broadcast and/or rebroadcast, prior to the audience becoming interested in the ad, or acting on the ad to generate a conversion event.
Matt Chalawsky